Configurable generic language understanding models

Abstract

Examples of the present disclosure describe systems and methods of configuring generic language understanding models. In aspects, one or more previously configured schemas for various applications may be identified and collected. A generic schema may be generated using the collected schemas. The collected schemas may be programmatically mapped to the generic schema. The generic schema may be used to train on ore more models. An interface may be provided to allow browsing the models. The interface may include a configuration mechanism that provides for selecting on or more of the models. The selected models may be bundled programmatically, such that the information and instructions needed to implement the models are configured programmatically. The bundled models may then be provided to a requestor.

1 . A system comprising:
 at least one processor; and   memory coupled to the at least one processor, the memory comprising computer executable instructions that, when executed by the at least one processor, performs a method for configuring language understanding models, the method comprising:
 receiving a request to create a generic schema; 
 collecting schema data associated with a first language understanding model and associated with a second language understanding model, wherein the schema data comprises a first set of domain data for a first domain identifier from a first domain and a second set of domain data from a second domain for a second domain identifier; 
 identifying a commonality of category between a first fine schema element in the first set of domain data and a second fine schema element in the second set of domain data; 
 mapping, in response to identifying the commonality, the first fine schema element and the second fine schema element to a third course schema element, wherein the third course schema element describes the identified commonality; 
 generating a generic schema using the collected schema data, wherein generating the generic schema comprises applying, to the generic schema, the mapping of the first fine schema element and the second fine schema element to the third course schema element; 
 using the generic schema data to train a plurality of language understanding models, wherein the training enables each of the plurality of language understanding models to process requests relating to the first domain and the second domain based on the mapping, wherein each of the plurality of language understanding models is trained using only a corresponding subset of course schema elements of the generic schema and fine schema elements from the first set of domain data and from the second set of domain data which were mapped to course schema elements in the corresponding subset of the generic schema, and wherein different language understanding models correspond to different subsets of course schema elements; and 
 providing an interface to view the plurality of language understanding models with the first domain and second domain. 
   
     
     
         2 . The system of  claim 1 , wherein collecting the schema data comprises:
 generating one or more data requests using the schema data;   transmitting the one or more data requests to one or more data stores; and   receiving schema data associated with the one or more data requests from the one or more data stores.   
     
     
         3 . The system of  claim 2 , wherein generating one or more data requests comprises:
 identifying mapping information, the mapping information indicating a relationship between one or more data sources and schema data known to be accessible by the one or more data sources; and   based on the mapping information, generating one or more specific data requests for the schema data known by the one or more data sources.   
     
     
         4 . The system of  claim 2 , wherein the received schema data comprises at least one of: model data, schema elements, an indication that the schema data is available, and information associated with the received schema data. 
     
     
         5 . The system of  claim 4 , wherein training the plurality of language understanding models comprises providing as input to the plurality of language understanding models at least one of: the generic schema, data used to generate the generic schema, and the received schema data. 
     
     
         6 . The system of  claim 5 , wherein providing the input comprises providing a first portion of the input to the first language understanding model and a second portion of the input to the second language understanding model. 
     
     
         7 . The system of  claim 1 , wherein generating the generic schema comprises:
 organizing the collected schema data by one or more categories;   converting the organized schema data into multi-dimensional representations of the schema data;   clustering the multi-dimensional representations into generic schema elements; and   mapping the clustered generic schema elements to the generic schema.   
     
     
         8 . The system of  claim 7 , wherein converting the organized schema data comprises applying canonical correlation analysis (CCA) to the organized schema data. 
     
     
         9 . The system of  claim 7 , wherein clustering the multi-dimensional representations comprises applying a k-means clustering algorithm to the multi-dimensional representations. 
     
     
         10 . The system of  claim 7 , wherein clustering the multi-dimensional representations comprises:
 identifying one or more terms in one or more multi-dimensional representations;   determining a generic term corresponding to the one or more terms; and   designating the generic term as a generic schema element.   
     
     
         11 . The system of  claim 1 , wherein the interface further provides for navigating, selecting, and bundling one or more trained language understanding models. 
     
     
         12 . The system of  claim 11 , wherein bundling the one or more trained language understanding models comprises:
 adding the one or more trained language understanding models to a bundle; and   adding instructions for automatically implementing the one or more trained language understanding models to the bundle.   
     
     
         13 . A method for configuring language understanding models, the method comprising:
 receiving a request to create a generic schema;   collecting schema data associated with a first language understanding model and associated with a second language understanding model, wherein the schema data comprises a first set of domain data for a first domain identifier from a first domain and a second set of domain data from a second domain for a second domain identifier;   identifying a commonality of category between a first fine schema element in the first set of domain data and a second fine schema element in the second set of domain data;   mapping, in response to identifying the commonality, the first fine schema element and the second fine schema element to a third course schema element, wherein the third course schema element describes the identified commonality;   generating a generic schema using the collected schema data, wherein generating the generic schema comprises applying, to the generic schema, the mapping of the first fine schema element and the second fine schema element to the third course schema element;   using the generic schema data to train a plurality of language understanding models, wherein the training enables each of the plurality of language understanding models to process requests relating to the first domain and the second domain based on the mapping, wherein each of the plurality of language understanding models is trained using only a corresponding subset of course schema elements of the generic schema and fine schema elements from the first set of domain data and from the second set of domain data which were mapped to course schema elements in the corresponding subset of the generic schema, and wherein different language understanding models correspond to different subsets of course schema elements; and   providing an interface to view the plurality of language understanding models with the first domain and second domain.   
     
     
         14 . The method of  claim 13 , wherein the schema data relates to at least one of: model information, schema information, query results, query generation information, domain confidence scores, and slot information. 
     
     
         15 . The method of  claim 13 , wherein collecting the schema data comprises:
 generating one or more data requests using the schema data;   determining one or more data stores known to the server device;   transmitting the one or more data requests to one or more known data stores; and   receiving schema data associated with the one or more data requests from the one or more known data stores.   
     
     
         16 . The method of  claim 13 , wherein generating the generic schema comprises:
 organizing the collected schema data by one or more categories;   converting the organized schema data into multi-dimensional representations of the schema data;   clustering the multi-dimensional representations into generic schema elements; and   mapping the clustered generic schema elements to the generic schema.   
     
     
         17 . The method of  claim 13 , wherein training the plurality of language understanding models comprises providing a first portion of the input to the first language understanding model and a second portion of the input to the second language understanding model. 
     
     
         18 . The method of  claim 17 , wherein the first language understanding model uses the first portion of the input to determine a first set of predictive relationships and the second language understanding model uses the second portion of the input to determine a second set of predictive relationships. 
     
     
         19 . The method of  claim 13 , wherein the interface further provides for navigating, selecting, and bundling one or more trained language understanding models, wherein the bundling comprises:
 adding the one or more trained language understanding models to a bundle; and   adding to the bundle instructions for automatically implementing the one or more trained language understanding models.   
     
     
         20 . A computer-readable media storing computer executable instructions that when executed cause a computing system to perform a method of configuring language understanding models, the method comprising:
 receiving a request to create a generic schema;   collecting schema data associated with a first language understanding model and associated with a second language understanding model, wherein collecting schema data comprises a first set of domain data for a first domain identifier from a first domain and a second set of domain data from a second domain for a second domain identifier;   identifying a commonality of category between a first fine schema element in the first set of domain data and a second fine schema element in the second set of domain data;   mapping, in response to identifying the commonality, the first fine schema element and the second fine schema element to a third course schema element, wherein the third course schema element describes the identified commonality;   generating a generic schema using the collected schema data, wherein generating the generic schema comprises applying, to the generic schema, the mapping of the first fine schema element and the second fine schema element to the third course schema element;   using the generic schema data to train a plurality of language understanding models, wherein the training enables each of the plurality of language understanding models to process requests relating to the first domain and the second domain based on the mapping, wherein each of the plurality of language understanding models is trained using only a corresponding subset of course schema elements of the generic schema and fine schema elements from the first set of domain data and from the second set of domain data which were mapped to course schema elements in the corresponding subset of the generic schema, and wherein different language understanding models correspond to different subsets of course schema elements; and   providing an interface to view the plurality of language understanding models with the first domain and second domain.